1. Field of the Invention
This invention relates to the use of ultraviolet laser-induced spectroscopy for analysis of mammalian tissue and, in particular, to the application of time-resolved, laser-induced, fluorescent spectroscopy for the characterization of tissue based upon the lipids and protein components in the tissue.
2. Description of the Related Arts
Laser-induced fluorescence spectroscopy (LIFS), and its applications to the medical field, diagnostic chemistry and other fields, have significantly evolved during the past 20 years. The increased interest in LIFS appears to be due to its ability to reveal both qualitative and quantitative information with respect to organic matter composition. Among the spectroscopic techniques, LIFS introduces several advantages, such as wavelength tunability, narrow bandwidth excitation, directivity, and short pulses excitation. LIFS selectively and efficiently excites the fluorophores in organic matter and greatly improves the fluorescence selectivity and detectability. For these reasons, LIFS techniques have found many applications in the above described fields.
Essentially, when ultraviolet (UV) laser light at a preselected frequency radiates upon, or excites, certain organic material, the return light that is reemitted from the material contains large amounts of information about the structural features and composition of the material. Several goals for the field of LIFS have been to extract this information 1) in a way that is sensitive enough to make fine and ultrafine distinctions between samples that have been previously difficult to distinguish--i.e. improved characterization; 2) rapidly, and even in real time, to those interested in analysis of the matter; 3) in a format that is readily interpretable or pre-interpreted via computer-assisted technologies; 4) at a low cost and 5) with tools (instruments) that are appropriate for the environment in which they are used (e.g. portability, small size). Ideally such a LIFS method and system would possess all of these characteristics.
Laser-induced fluorescence emission can be conveniently divided into its static (steady-state) and dynamic (time- and frequency-domain) forms. The static form provides information of particular features such as: 1) intensity (e.g., concentration of species, quenching of species); 2) spectral distribution (e.g., information on the local environment surrounding the fluorophore, number of emitting components); and 3) polarization/anisotropy (e.g., average size of rotationally mobile species, protein-ligand binding). The dynamic form furnishes information such as: 1) excited-state intensity decay or fluorescence lifetime (e.g., it can resolve static emission into contributions from the individual fluorophores, study kinetic processes, elucidate origin of quenching processes); and 2) anisotropy (e.g., detailed reorientational dynamics of nonspherical rotors).
Steady State LIFS
The detection and the classification of organic matter have been mostly based on analysis of steady-state spectra. For example, in the bioengineering field, several studies introduced the idea of incorporating spectroscopic guidance into clinical fiber optic system to guide angioplasty systems. This technique provides an "integral" spectrum over time which gives information about emission availability and identification. The spectrum can be recorded with the help of an Optical Multichannel Analyzer (OMA) or by a scanning monochromator. Generally, scanning the spectrum by means of a monochromator is more convenient, although at a specific time only the light of a particular wavelength is recorded. This disadvantage is compensated by the superior sensitivity of photodetectors available and by their linear response in contrast to the diode array used by an OMA system. However, with steady state systems, the time dependence of emission and the potential information contained therein are ignored.
Time-Resolved LIFS (TR-LIFS)
TR-LIFS is a less explored technique for investigation of organic matter fluorescence. However, the progress of short (nanoseconds) and ultra-short (picoseconds) pulsed lasers has generated a growing interest in this field. For example, fluorescence decay of various amino acids (i.e., tyrosine, tryptophan and phenylalanine) has been an important analytical tool for protein structure and environment studies. By monitoring the fluorescence lifetime, information about the structure of the protein can be extracted. This information can be complementary to spectral information when complex biological systems, such as tissue samples, are investigated.
TR-LIFS records information regarding the emission (fluorescence pulse response) which occurs in a short time interval after the stimulating event (excitation pulse). Therefore, it permits separation of "early" (usually direct excitation of short-lived states or very rapid subsequent reactions) and "late" (usually from long-lived states, delayed excitation by persisting electron populations or by reactions which follow the original electron process) processes, referred to as the stimulus time. Fluorescence lifetime is defined as the time required for the fluorescence emission to decay to l/e of its initial intensity. Direct measurements of fluorescence lifetime is based on the assumption that this process follows first-order kinetics quantitatively described by equation: EQU I.sub.t =I.sub.0 e.sup.-t/.tau.
where I.sub.0 and I.sub.t are the fluorescence intensities at times zero and .tau., respectively.
The measured fluorescence decay of a fluorophore excited by a short pulse of light is a convolution of the excitation pulse shape (distorted by the detection system) with the true fluorescence decay (fluorescence impulse response function (FIRF)): EQU y(t)=.intg..sub.0 I.sub.f (.tau.)x(t-.tau.)d.tau.
Since accurate determination of the fluorescence impulse response is an important issue for time-resolved studies, numerous deconvolution techniques, such as Least-squares iterative reconvolution method, method of moments, Laplace Transforms, and Fourier Transforms have been developed and are well known in the art.
Application to the Characterization of Diseased Tissue
Atherosclerosis, a progressive disease of blood vessels, is reported to be the leading cause of death during middle and late adulthood in economically advanced societies. It has predilection for the critical arterial beds (coronary, cerebral and aortoiliac) and leads to critical events such as myocardial infarction, stroke, and ischemic gangrene of the extremities. Intensive efforts have been made to characterize atherosclerotic lesions in clinical situations. The main task for a technique designed to perform a clinical classification of the lesions is to picture as closely as possible the histological classification. The resulting information could then be used to accurately determine a treatment for a specific lesion type. The same holds true for other tissue diseases such as tumors. Although various techniques have been employed for clinical classification and imaging, clinical assessment of atherosclerotic lesions has been limited. Some have evaluated aneurysms and estimation of severity of stenosis. However, prevention of complicated lesions that lead to critical events, such as acute coronary syndrome, requires early detection of lesions and assessment of lesions extent. With respect to this issue, recent reports of American Heart Association have suggested that clinical danger is not very well correlated with the degree of stenosis or plaque size, but rather with plaque composition. The reports have emphasized the actual need for (1) quantitative data on size and consistency of the lipid-rich core of the fibrous plaque; and (2) greater sensitivity of imaging methods to detect and measure the components of small and thin fibrous plaques, especially those with relatively large lipid-rich centers which are likely to lead to serious clinical events such as rupture.
One research team from M.I.T. has identified that it is possible to diagnosis the presence of atherosclerosis in the human artery wall with the application of time resolved fluorescence spectroscopy. See Baraga et al. "Ultraviolet Laser Induced Fluorescence of Human Aorta, Spectrochim. Acta 45:95-99, 1989; and U.S. Pat. No. 5, 419,323 to Kittre II et al., and assigned to M.I.T. Others have put forth efforts to improve predictive and diagnostic methods of malignant tissue.
Unfortunately, these studies tended to focus upon the study of the known intrinsic fluorophores in tissue matter, namely collagen and elastin, but generally ignored the effect of lipids in the matter. Another primary drawback of the TR-LIFS (time domain) methods described in the literature has been one of lack of robustness and sensitivity. While the early studies of the composition of a variety of matter using TR-LIFS have shown promise, these described methods have been limited to binary classifications, that is, to crudely identify merely whether or not a particular substance of interest is present in the sample. Moreover, one reason for the limited application of fluorescence spectroscopy for tissue diagnostics is that the measured fluorescence is distorted by the effects of tissue optical properties (i.e., absorption and scattering).
Accordingly, a more precise and sensitive methodology is needed that can discriminate between a given tissue type in its varying stages of disease. For example, a TR-LIFS technique that can discern between the eight types of lesions categorized by the American Heart Association in the progressive heart disease of atherosclerosis, would be a tremendously valuable supplement to the above described binary classification systems.
Another drawback with prior TR-LIFS methodologies is that they tended to study the fluorescent tissue characteristics only at a limited number of discrete wavelengths. Much more robust information about tissue structure and condition can be gleaned with analysis of the tissue across an entire spectrum of wavelengths.
Thus a need exists for a sensitive method and system capable of quantitatively, as well as qualitatively, analyzing all of the influential fluorescent tissue components (collagen, elastin and lipids) that contribute to the character of tissue in their normal, healthy stages and in each of their classifiable diseased stages.